Re: Clustering
- To: mathgroup at smc.vnet.net
- Subject: [mg128008] Re: Clustering
- From: Nigel King <nigel.king at cambiumnetworks.com>
- Date: Sat, 8 Sep 2012 03:10:28 -0400 (EDT)
- Delivered-to: l-mathgroup@mail-archive0.wolfram.com
- Delivered-to: l-mathgroup@wolfram.com
- Delivered-to: mathgroup-newout@smc.vnet.net
- Delivered-to: mathgroup-newsend@smc.vnet.net
- References: <20120906081314.D511E683B@smc.vnet.net>
Hi Bob,
Thank you very much for this.
For some reason I had dismissed Method->"Agglomerate" thinking that it was
the default method.
Sorry for troubling you.
Nigel King
On 7 Sep 2012, at 09:59, Bob Hanlon wrote:
data1 = {10996160116271, 10996160121402, 10996159625418,
10996162114125, 10996160124050, 10996162119731, 10996162119161,
10996162119412, 10996159624663, 10996159625205, 10996162082868,
10996159624249, 10996162084724, 10996162091672, 10996162117101,
10996162100233, 10996162119612, 10996163806869, 10996162119594,
10996160176675, 10996160176687, 10996160176724, 10996160176645,
10996162120528, 10996160157953, 10996160147558, 10996160159628,
10996160158103, 10996160153768, 10996160158093, 10996160147558,
10996162118276, 10996162119018, 10996163808057, 10996163808139,
10996163807032, 10996162122560, 10996162068604, 10996162127032,
10996162119426, 10996162119433, 10996162119039, 10996162119429,
10996162118843, 10996162119436, 10996162120269, 10996162119583,
10996162120271, 10996162120255, 10996162119663, 10996162064880,
10996162120272, 10996162120224, 10996162119666, 10996163810937,
10996162118985, 10996162119234, 10996160158214, 10996163810862,
10996162119390, 10996162119218, 10996162119211, 10996162119144,
10996162119264, 10996162119046, 10996162119267, 10996162120316,
10996162119425, 10996162119536, 10996162119071, 10996162119346,
10996162120402, 10996162119091, 10996162119030, 10996162119499,
10996162115558, 10996162119337, 10996162119035, 10996162119534,
10996162117042, 10996162119215, 10996162119393, 10996162118962,
10996159624797, 10996162120344, 10996162119377, 10996162120222,
10996162120223, 10996162119407, 10996162120246, 10996162120279,
10996162120326, 10996162119994, 10996162120057, 10996162120294,
10996162119880, 10996162119513, 10996162119803, 10996160145836,
10996160136827, 10996162068121, 10996162078289, 10996159618487,
10996159623760, 10996159624293, 10996160180483, 10996159624759,
10996162118806, 10996160181693, 10996159623760, 10996159624411,
10996160116463, 10996159618114, 10996160162419, 10996160160562,
10996160121379, 10996160125728, 10996160168867, 10996160142681,
10996160168532, 10996160168551, 10996160150082, 10996159625337,
10996159625454};
ListPlot[data1,
PlotRange -> All, ImageSize -> 300,
Frame -> True, Axes -> False]
clu = FindClusters[data1, Method -> "Agglomerate"];
clu4 = FindClusters[data1, 4, Method -> "Agglomerate"];
clu === clu4
True
ListPlot[clu,
PlotRange -> All, ImageSize -> 300,
Frame -> True, Axes -> False]
curveColor[n_Integer] :=
Hue[Mod[2/3 - 2 + Sqrt[5]*(n - 1), 1], 0.6, 0.6];
Clear[plt]
plt[v_, color_: curveColor[1]] := ListPlot[
Sort[v] - Median[v],
PlotRange -> All, ImageSize -> 300,
Frame -> True, Axes -> False,
PlotStyle -> color]
plt[data1]
n = 1; Column[plots =
(plt[#, curveColor[n++]] & /@ clu)]
Show[plots]
ListPlot[
Sort[#] - Median[#] & /@ clu,
PlotRange -> All, ImageSize -> 300,
Frame -> True, Axes -> False]
Bob Hanlon
On Thu, Sep 6, 2012 at 4:13 AM, Nigel King
<nigel.king at cambiumnetworks.com> wrote:
> Hi All,
> The following short program has some data which looks visually as though
it would separate into 4 groups by the use of the command FindClusters. You can see the use of that command in the lines below but, the data has not separated as I would have expected. I realise that I do not know how to use the various clustering components of mathematica to do this. Any insight would be useful.
>
> Thanks
>
> Nigel King
>
>
> data1 = {10996160116271, 10996160121402, 10996159625418, 10996162114125,
> 10996160124050, 10996162119731, 10996162119161, 10996162119412,
> 10996159624663, 10996159625205, 10996162082868, 10996159624249,
> 10996162084724, 10996162091672, 10996162117101, 10996162100233,
> 10996162119612, 10996163806869, 10996162119594, 10996160176675,
> 10996160176687, 10996160176724, 10996160176645, 10996162120528,
> 10996160157953, 10996160147558, 10996160159628, 10996160158103,
> 10996160153768, 10996160158093, 10996160147558, 10996162118276,
> 10996162119018, 10996163808057, 10996163808139, 10996163807032,
> 10996162122560, 10996162068604, 10996162127032, 10996162119426,
> 10996162119433, 10996162119039, 10996162119429, 10996162118843,
> 10996162119436, 10996162120269, 10996162119583, 10996162120271,
> 10996162120255, 10996162119663, 10996162064880, 10996162120272,
> 10996162120224, 10996162119666, 10996163810937, 10996162118985,
> 10996162119234, 10996160158214, 10996163810862, 10996162119390,
> 10996162119218, 10996162119211, 10996162119144, 10996162119264,
> 10996162119046, 10996162119267, 10996162120316, 10996162119425,
> 10996162119536, 10996162119071, 10996162119346, 10996162120402,
> 10996162119091, 10996162119030, 10996162119499, 10996162115558,
> 10996162119337, 10996162119035, 10996162119534, 10996162117042,
> 10996162119215, 10996162119393, 10996162118962, 10996159624797,
> 10996162120344, 10996162119377, 10996162120222, 10996162120223,
> 10996162119407, 10996162120246, 10996162120279, 10996162120326,
> 10996162119994, 10996162120057, 10996162120294, 10996162119880,
> 10996162119513, 10996162119803, 10996160145836, 10996160136827,
> 10996162068121, 10996162078289, 10996159618487, 10996159623760,
> 10996159624293, 10996160180483, 10996159624759, 10996162118806,
> 10996160181693, 10996159623760, 10996159624411, 10996160116463,
> 10996159618114, 10996160162419, 10996160160562, 10996160121379,
> 10996160125728, 10996160168867, 10996160142681, 10996160168532,
> 10996160168551, 10996160150082, 10996159625337, 10996159625454};
> clu = FindClusters[data1, 4, Method -> "Optimize"];
> plt[v_] :=
> ListPlot[Sort[v] - Median[v], PlotRange -> All, ImageSize -> 300,
> Frame -> True, Axes -> False]
> plt[data1]
> Map[plt, c1u] // Column=
>
>
- References:
- Clustering
- From: Nigel King <nigel.king@cambiumnetworks.com>
- Clustering